Fourth generation wireless communications networks have a requirement of a high data throughput, for example one Gbits/s. In order to accomplish this, some systems utilize spatial multiplexed Single User Multiple Input, Multiple Output (SU-MIMO) communication to increase the data throughput.
For downlink (DL) communication, the Long Term Evolution-Advanced (LTE-A) working bodies have agreed utilize a Minimal Mean Squared Error (MMSE) MIMO detection algorithm as a benchmark in the default evaluation algorithm for a downlink receiver. Further, more advanced MIMO receiver algorithms such as a Maximum Likelihood Detector (MLD) or Turbo-Successive-Interference-Cancellation (Turbo-SIC) algorithms may be used in the Long Term Evolution (LTE) uplink and downlink.
One challenge with MIMO detection algorithms is that a tradeoff exists between good performance and low computational complexity. For example, the MMSE. MIMO detection algorithm has a relatively low complexity but its performance is not optimal. On the other hand, the maximum likelihood (ML) MIMO detector algorithm has better performance among non-iterative algorithms, but its complexity is prohibitively high when modulation order and MIMO order are high.